The computation of the Manhattan distance between vectors, defined as ##EQU1## where N is the number of dimensions of the vector, is a common operation in different fields, ranging from signal processing to pattern recognition. When this function is embedded in portable systems it is highly desirable to reduce the power consumption associated with the computation. Most portable systems are digital in nature. Consequently, the calculation of the Manhattan distance in a given application is computed digitally. It is difficult to optimize the digital calculation of a Manhattan distance to reduce power consumption.